Oxford, GB / San Francisco, CA, US

You must have extensive experience in Computer Vision with specialization in at least one of the following areas:

Dense Mapping: Design and implement advanced algorithms for reconstructing dense 3D models of large-scale indoor environments using depth sensors.

Sparse SLAM: Design and implement advanced algorithms for mapping and tracking in large environments using sparse maps.

Visual-Inertial Pose Tracking: Design and implement advanced algorithms for estimating the 3D pose of a head-mounted device by optimally fusing visual and inertial measurements collected from multiple cameras and IMUs.

3D Scene Understanding: Design and implement 3D scene segmentation algorithms based on depth, motion or texture data.

3D Object Tracking: Design and implement robust algorithms for detecting and tracking the 6 DOF pose of known moving objects from multiple cameras in presence of clutter and occlusions.


- Expert knowledge in at least one area listed above: 
- Fluent in C/C++ (programming and debugging) 
- Experience working with OpenCV and OpenGL 
- Knowledge of parallel computing, OpenCL, GPGPU is a plus 
- Knowledge software optimization and embedded programming is a plus 
- Mobile Platform Software Engineering (Android NDK, IOS Metal)


Ph.D. in Computer Science or Electrical Engineering 
Post Doctoral Research in 3D Computer Vision is preferred